Radiology

Detecting Adverse Pathology of Prostate Cancer With a Deep Learning Approach Based on a 3D Swin-Transformer Model and Biparametric MRI: A Multicenter Retrospective Study.

BACKGROUND: Accurately detecting adverse pathology (AP) presence in prostate cancer patients is impo...

Reference standard for the evaluation of automatic segmentation algorithms: Quantification of inter observer variability of manual delineation of prostate contour on MRI.

PURPOSE: The purpose of this study was to investigate the relationship between inter-reader variabil...

The Relationship Between Artificial Intelligence-Assisted OCT Angiography-Derived Foveal Avascular Zone Parameters and Visual-Field Defect Progression in Eyes with Open-Angle Glaucoma.

PURPOSE: To investigate clinical factors associated with foveal avascular zone (FAZ) parameters obta...

Incremental learning for an evolving stream of medical ultrasound images via counterfactual thinking.

Despite the fact that traditional deep learning (DL) approaches provide promising accuracy and effic...

3D Breast Cancer Segmentation in DCE-MRI Using Deep Learning With Weak Annotation.

BACKGROUND: Deep learning models require large-scale training to perform confidently, but obtaining ...

Noninvasive identification of HER2-low-positive status by MRI-based deep learning radiomics predicts the disease-free survival of patients with breast cancer.

OBJECTIVE: This study aimed to establish a MRI-based deep learning radiomics (DLR) signature to pred...

CardioVision: A fully automated deep learning package for medical image segmentation and reconstruction generating digital twins for patients with aortic stenosis.

Aortic stenosis (AS) is the most prevalent heart valve disease in western countries that poses a sig...

A Deep Learning Model Enhances Clinicians' Diagnostic Accuracy to More Than 96% for Anterior Cruciate Ligament Ruptures on Magnetic Resonance Imaging.

PURPOSE: To develop a deep learning model to accurately detect anterior cruciate ligament (ACL) rupt...

Applying deep learning to recognize the properties of vitreous opacity in ophthalmic ultrasound images.

BACKGROUND: To explore the feasibility of artificial intelligence technology based on deep learning ...

Multimodality deep learning radiomics nomogram for preoperative prediction of malignancy of breast cancer: a multicenter study.

. Breast cancer is the most prevalent cancer diagnosed in women worldwide. Accurately and efficientl...

Value of Imaging in the Non-Invasive Prediction of Recurrence after Catheter Ablation in Patients with Atrial Fibrillation: An Up-to-Date Review.

Catheter ablation (CA) is the first-line treatment for atrial fibrillation (AF) patients. However, t...

Systematic review of artificial intelligence development and evaluation for MRI diagnosis of knee ligament or meniscus tears.

OBJECTIVE: The purpose of this systematic review was to summarize the results of original research s...

The International Association for the Study of Lung Cancer Early Lung Imaging Confederation Open-Source Deep Learning and Quantitative Measurement Initiative.

INTRODUCTION: With global adoption of computed tomography (CT) lung cancer screening, there is incre...

Automated Deep Learning-Based Segmentation of Abdominal Adipose Tissue on Dixon MRI in Adolescents: A Prospective Population-Based Study.

The prevalence of childhood obesity has increased significantly worldwide, highlighting a need for ...

Timing intrauterine inseminations: Do we need an ultrasound, or can artificial intelligence do the trick?

Deep learning-based automated lesion segmentation on mouse stroke magnetic resonance images.

Magnetic resonance imaging (MRI) is widely used for ischemic stroke lesion detection in mice. A chal...

Closing the loop for AI-ready radiology.

BACKGROUND: In recent years, AI has made significant advancements in medical diagnosis and prognosis...

Attention-guided multi-scale learning network for automatic prostate and tumor segmentation on MRI.

BACKGROUND AND OBJECTIVE: Image-guided clinical diagnosis can be achieved by automatically and accur...

Deep learning-based reconstruction for canine brain magnetic resonance imaging could improve image quality while reducing scan time.

Optimal magnetic resonance imaging (MRI) quality and shorter scan time are challenging to achieve in...

Rapid Quantification of Microvessels of Three-Dimensional Blood-Brain Barrier Model Using Optical Coherence Tomography and Deep Learning Algorithm.

The blood-brain barrier (BBB) is a selective barrier that controls the transport between the blood a...

Mammography using low-frequency electromagnetic fields with deep learning.

In this paper, a novel technique for detecting female breast anomalous tissues is presented and vali...